TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	4
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Understand biological databases, advanced and multiple sequence alignment strategies, and models and algorithms of sequence alignments. 2) Learn advanced sequence and domain prediction, and molecular phylogenetic strategies. 3) Understand protein and RNA structure prediction approaches. 4) Perform computer application of the course content, run a study on individual basis, and discuss results.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Bioinformatics, compiling and analyzing complex biological data in the context of the synthesis of the fields of mathematics, statistics, computer science, molecular biology and genetics in order to make sense of, store, and visualize biological data and to make maximum use of this enormous knowledge, It is also intended to relate approaches between genomic and proteomic data.
COURSE CONTENTS	WEEK TOPICS 1st Week Biological Databases 2nd Week Multiple Sequence Alignments and Models 3rd Week Computer Applications 4th Week Promoter and Regulatory Sequence Prediction 5th Week Protein Motifs and Domain Prediction 6th Week Computer Applications 7th Week Phylogenetic Tree Construction Methods and Programs 8th Week MIDTERM 9th Week Computer Applications 10th Week Comparison of Protein Structures 11th Week Prediction of Protein Structures 12th Week Prediction of Secondary RNA Structures 13th Week Computer Applications 14th Week Student Projects and Discussions
RECOMENDED OR REQUIRED READING	Essential Bioinformatics. Jin Xiong. Cambridge University Press, 2006.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Discussion,Practice,Project
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Practice 1 25 Total(%) 60 Contribution of In-term Studies to Overall Grade(%) 60 Contribution of Final Examination to Overall Grade(%) 40 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 1 14 Preparation for Final exam 1 30 30 Course hours 13 2 26 Preparation for Midterm exam 1 25 25 Laboratory (including preparation) Final exam 1 2 2 Homework Performance Practice 13 2 26 Total Workload 125 Total Workload / 30 4,16 ECTS Credits of the Course 4
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No